Difference between revisions of "Admin-set-resource-quota-dynamically"
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== Introduction == | == Introduction == | ||
| − | To achieve high cost-effectiveness in IaaS cloud operation, a cloud administrator tries to save physical resources <br /> | + | To achieve high cost-effectiveness in IaaS cloud operation, a cloud administrator tries to save physical resources while<br /> |
| − | + | guaranteeing users' QoS requirements. After more and more IaaS clouds are deployed, cost-effectiveness in IaaS operation<br /> | |
| − | + | has become an important problem, attracting attention from both public and private cloud owners and administrators. | |
Highly cost-effective IaaS operation requires allocating physical resource quota to a VM instance quantitativelyand accurately,<br /> | Highly cost-effective IaaS operation requires allocating physical resource quota to a VM instance quantitativelyand accurately,<br /> | ||
| Line 17: | Line 17: | ||
parameters, e.g. VCPU number, can be specified. | parameters, e.g. VCPU number, can be specified. | ||
| − | According to the requirements derived from our IaaS operation practices, we come to recognize that there is still <br /> | + | According to the requirements derived from our IaaS operation practices, we come to recognize that there is still space left for<br /> |
| − | + | further improvement in instance-level physical resource quota allocation. Except for the capability of static instance quota allocation,<br /> | |
| − | + | dynamic instance quota adjustment is also valuable for cloud administrators. With such dynamic adjustment capability, they can<br /> | |
| − | dynamic adjustment capability, they can re-allocate resources according to requirements when instances are running. | + | re-allocate resources according to requirements when instances are running. As an example, the admin can allocate more physical<br /> |
| − | As an example, the admin can allocate more physical CPU execution time to a high-priority instance running computation-intensive | + | CPU execution time to a high-priority instance running computation-intensive or latency-critical workloads. Also, more blkio bandwidth<br /> |
| − | or latency- | + | could be allocated to high-poiority instances running I/O-intensive workloads. Combining the dynamic adjustment capability with the<br /> |
| − | workloads. Combining the dynamic adjustment capability with the existing static allocation capability, such resource allocation | + | existing static allocation capability, such resource allocation decisions can be made either before or after instances are created. |
| − | decisions can be made either before or after instances are created. | ||
| − | In this blueprint, we propose the capability of dynamically adjusting available physical resources, e.g. CPU execution <br /> | + | In this blueprint, we propose the capability of dynamically adjusting available physical resources, e.g. CPU execution time for VCPU<br /> |
| − | + | of an instance, physical memory occupation, disk I/O bandwidth, etc. With this feature, it can be decided quantitatively that how much<br /> | |
| − | + | physical resources should be allocated and reserved to an instance when it is running. | |
---- | ---- | ||
[[Category:Spec]] | [[Category:Spec]] | ||
Revision as of 08:04, 18 September 2013
- Launchpad Entry: NovaSpec:admin-set-resource-quota-dynamically
- Created: Sep. 18, 2013
- Contributors: Yu Zhang
Introduction
To achieve high cost-effectiveness in IaaS cloud operation, a cloud administrator tries to save physical resources while
guaranteeing users' QoS requirements. After more and more IaaS clouds are deployed, cost-effectiveness in IaaS operation
has become an important problem, attracting attention from both public and private cloud owners and administrators.
Highly cost-effective IaaS operation requires allocating physical resource quota to a VM instance quantitativelyand accurately,
e.g. physical CPU execution time, physical memory limitation, blkio and network bandwidth. From Grizzly, OpenStack introduces
the feature of Instance Resource Quota, which provides the capability of static instance quota allocation.
With this feature, a quantitative and accurate resource quota can be assigned and reserved for an instance statically when it is
created. This feature is a large improvement to the basic resource allocation mechanism in OpenStack, in which only fundamental
parameters, e.g. VCPU number, can be specified.
According to the requirements derived from our IaaS operation practices, we come to recognize that there is still space left for
further improvement in instance-level physical resource quota allocation. Except for the capability of static instance quota allocation,
dynamic instance quota adjustment is also valuable for cloud administrators. With such dynamic adjustment capability, they can
re-allocate resources according to requirements when instances are running. As an example, the admin can allocate more physical
CPU execution time to a high-priority instance running computation-intensive or latency-critical workloads. Also, more blkio bandwidth
could be allocated to high-poiority instances running I/O-intensive workloads. Combining the dynamic adjustment capability with the
existing static allocation capability, such resource allocation decisions can be made either before or after instances are created.
In this blueprint, we propose the capability of dynamically adjusting available physical resources, e.g. CPU execution time for VCPU
of an instance, physical memory occupation, disk I/O bandwidth, etc. With this feature, it can be decided quantitatively that how much
physical resources should be allocated and reserved to an instance when it is running.
